3 key considerations for successfully deploying AI for customer care

In case you missed it, Cresta CMO Scott Kolman was recently joined by Sheryl Kingstone, analyst with 451 Research on our webinar: Navigating Customer Experience with Generative AI: Do’s and Don’ts. In the webinar, Sheryl and Scott dug into macroeconomic trends and major shifts in consumer behavioral priorities to understand the true impact that generative AI can have on customer care. Most importantly, they provided a guide to attendees on how to successfully implement AI to drive better outcomes in customer care and experience. 

Read on for three things to reflect on before you put generative AI to work for your customer strategy. 

Build, don’t buy

The introduction of public LLMs – such as those offered by OpenAI, Anthrophic, Microsoft, Google, and others – make it possible for organizations to build basic generative AI proofs of concept. However, here are a couple serious considerations to bear in mind when it comes to deciding whether to build or buy: 

  • Building AI in-house has unforeseen complexity
    An incredible amount of expertise and experience goes into building these types of models. Some of the things you need to consider? The various CX systems the data will flow through and how you set up your architecture, experience in your organization with working with LLMs, model selection and sizing – for cost, latency, and task performance. As you can see, building in-house effectively is a very nuanced process and should not be undertaken lightly.  
  • There is a tremendous opportunity cost to building your own AI
    Cost containment is a significant priority for businesses right now – in fact, 46% have shifted from a focus on revenue growth to cost reduction. For companies that are looking to develop this from the ground up, they need to be aware of the incredible time and resource investment they have ahead of them. Cresta has been building our own AI for years with an incredible bench of talent and expertise – and we are still accelerating. 

    You can learn more about Cresta’s journey with LLMs for the enterprise here. Also, remember that there are opportunities to ‘build with’; Cresta’s approach to deploying our technology allows for a wide range of external integrations and webhook functionality. 

Learn more here where we break down the pros and cons of building your own generative AI solution

Emotion is the currency of experience

It’s not groundbreaking to hear that agents play a critical role in handling customer emotions; more than ever, contact center agents are the ‘face’ of a company and managing a customer’s experience is a significant part of their role. However, to handle this responsibility, agents need to be effectively trained and prepared. As generative AI takes on the more repetitive and basic tasks in a contact center environment, agents are expected to deal with more complex issues – including handling more of the emotionally-charged issues that customers may have. 

Generative AI can understand up-front what topics and issues result in different customer emotions and sentiment. Through a combination of keyword and LLM analysis of a conversation, agents get this information – all in real time. This instant analysis helps agents to understand when sentiment is positive, negative, or neutral, and also gives nuance to the emotions happening in a conversation. Agents get instant insight into when a customer is frustrated, disappointed, confused, or happy. 

Generative AI can then help a team create rules that can be proactively triggered during a customer conversation that will help agents navigate conversations. This can include alerts, real-time guidance, effective and targeted coaching, and a more modern approach to quality management (QM). 

Scale efficiencies through AI 

To make your deployment as effective as possible, identify the top areas of potential to start with. According to Sheryl’s research, employee experience and customer experience are driving the top transformation objectives right now. 

As discussed above, AI for customer care use case can provide contact center agents with the insights, hints, tips, and even in-the-moment guidance through workflows that will help them rapidly resolve a customer issue. This not only gives customers a much more streamlined, consistent experience across the agents they engage with, but also saves them time.

For employees, AI has tremendous potential to improve workforce productivity and engagement. One huge benefit – particularly as contact centers grapple with one of the highest attrition rates – is the ability to speed up new agent onboarding through real-time guidance during customer interactions as they learn the business, products, and services. For more veteran employees, generative AI helps to reduce their cognitive load, and increase their time to respond to customers by allowing them to seamlessly tap into knowledge base information that is surfaced as they need it. 

For the business more broadly, generative AI can help reduce costs through operational efficiencies, including the reduction or total elimination of after-call work. 

There are many other ways that leveraging generative AI can help to improve the business from all sides. To see a customized demo of how Cresta can holistically improve your approach to customer care, driving sales, and better operations, get in touch now

Download the on-demand replay now to get even more insight: Navigating Customer Experience with Generative AI: Do’s and Don’ts.